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Semantic Methods for Electronic Markets
Rudi Studer1,2,3, Anupriya Ankolekar1,2, Nenad
Stojanovic2
Institute AIFB, University of Karlsruhewww.aifb.uni-karlsruhe.de/WBS
FZI Research Center for Information Technologies
www.fzi.de
Ontoprise GmbHwww.ontoprise.de
SRI, Menlo ParkAugust 10, 2006
August 10th, 2006, SRI 2
Outline
• Semantic Technologies and Services @ Karlsruhe
• Services Vision and its Challenges• Semantic Services
– Service Matching: Discovery and Selection– Semantic Business Process Management– Semantic Compliance Management
• Conclusion
August 10th, 2006, SRI 3
Karlsruhe: Location for Semantic Technologies
Knowledge Management
Community Support
Electronic Markets
eGovernment
Semantic Web Infrastructure
Ontology Management
Data and Text Mining
Peer-to-Peer
Semantic Web Services
Application-orientedResearch
Know-how TransferRealizing new Scenarios
Application-orientedResearch
Product DevelopmentInnovative Solutions
Basic ResearchApplication-oriented
Research
AIFB
August 10th, 2006, SRI 4
Who are we? … Semantic Technologies Research Group
FZIAIFB
Rudi Studer
Valentin Zacharias
Max Völkel
Nenad Stojanovic
York Sure
Andreas Abecker
Ljiljana Stojanovic
Johanna Völker
Stephan Bloehdorn
Sudhir Agarwal
Jens Hartmann
Philipp Cimiano
Mark Hefke
Stephan GrimmPeter Haase
Steffen Lamparter
Saartje Brockmans
Pascal Hitzler
Denny Vrandecic
Christoph Tempich
Markus Krötzsch
Anupriya Ankolekar
Hans-Jörg Happel
Heiko Haller
Holger Lewen
Sebastian Blohm
Yimin Wang
Julien Tane
Knowledge Management
Community Support
Electronic Markets
eGovernment
Ontology Management
Data/Text Mining
Peer-to-Peer
Semantic Web Services
Simone Braun
& ~40 people at Ontoprise
Sebastian Rudolph
Duc Thanh Tran
Tuvshintur Tserendorj
August 10th, 2006, SRI 5
Semantic Web Services Projects
SmartWeb Mediating mobile, intelligent access to Web services, such as weather, route information etc.
DIP Data, Information, and Process Integration with Semantic Web Services Reasoning infrastructure for Semantic Web services
SESAM Semantic matching of energy products and legal contracts in P2P electricity markets
IME Graduate school of information management and market engineering
– Ontology-based policies for buyer preferences and seller pricing– Mapping between different ontology and rule formalisms and their visual
modelling via meta-modeling
Billing the Grid Accounting and pricing resource usage in Grid environments based on negotiation and policies
FIT Fostering self-adaptive e-government service Improvement using semantic Technologies SAKE Semantic-enabled Agile Knowledge-based e-government
SAP Cooperation projects in the context of SOA
August 10th, 2006, SRI 6
Outline
• Semantic Technologies and Services @ Karlsruhe
• Services Vision and its Challenges• Semantic Services
– Service Matching: Discovery and Selection– Semantic Business Process Management– Semantic Compliance Management
• Conclusion
August 10th, 2006, SRI 7
The vision of a service-oriented world
• Automated B2B commerce• Electronic trading
marketplaces • Business process outsourcing
and integration on the Web• Resource sharing, distributed
computation• Company eco-systems
August 10th, 2006, SRI 8
Challenges
1. How to discover the right services?– For my business needs and objectives– UDDI common solution, but insufficient: need
programmer agreement, search through keywords
2. How to compose services (automatically)?– Create plan or template with unknown and/or
unreliable services (planning operators)– Service composition needs to go beyond functional
composition for real business needs
3. How to select the services to invoke or serve?– Multi-attributive services with differing QoS
August 10th, 2006, SRI 9
Challenges
4. How can services talk to each other?– Interoperability of data, protocols, processes,
applications– Common standards help, but manual agreement
still required
5. How to establish trust among the participants of a transaction?– legal responsibilities of participants
August 10th, 2006, SRI 10
Our approach: Semantic Services
Semantic annotations and reasoning to address several challenges:
1. How to discover the right services?– semantics for richer descriptions of services for
automated, more accurate service discovery
2. How to compose services (automatically)?– semantic service descriptions for automated
composition, incl. preconditions and effects – semantic descriptions of constraints and goals
3. How to select the services to invoke or serve?– Semantic description of multi-attribute services and
preferences used for selection decision
August 10th, 2006, SRI 11
Our approach: Semantic Services
4. How can services talk to each other?– Semantic interoperability via the use of shared
expressive ontologies for modelling services
5. How to establish trust among the participants of a transaction?– On-the-fly contracting using semantic contract
descriptions– Reputation mechanisms
August 10th, 2006, SRI 12
Outline
• Semantic Technologies and Services @ Karlsruhe
• Services Vision and its Challenges• Semantic Services
– Service Matching: Discovery and Selection
– Semantic Business Process Management– Semantic Compliance Management
• Conclusion
August 10th, 2006, SRI 13
Scenario: Matchmaking
Which service can I use to generate optimal routing as part of my Order-To-Cash business process?
Provider 1
Provider 2
Provider n
Sales order
Delivery
Picking
Shipment
Packing
RoutingService Discovery• Need service that can fit
in existing workflows• Real business needs go
beyond functional matching of services, e.g. for Business Process Outsourcing
August 10th, 2006, SRI 14
Approach
• Model services (offers) and requests declaratively in terms of – Functional and temporal attributes– Service configurations– Preconditions and desired effects/actions of
services
– Business policies, access control policies etc.
• Matchmaking answers include conditions under which a service is a match
[see publications by Agarwal, Ankolekar, Lamparter]
functional
context-driven
August 10th, 2006, SRI 15
Modelling Web Services
• Describe temporal structure of a web service with -calculus– Composition is a central aspect of -calculus
– Typed communication channels can capture relationships between input and output activities
– Describe involved objects (-calculus names) semantically with description logics
– Embed access control policies as -calculus conditions
August 10th, 2006, SRI 16
Scenario: Matchmaking
Which service can I use to generate optimal routing as part of my Order-To-Cash business process? Provider 1
Provider 2
Provider n
Sales order
Delivery
Picking
Shipment
Packing
Routing
Service Selection• How to choose which service to
use?• Select best service from set of
matching services– Preference-based selection for
configurable services– Auctions for globally optimal
service allocation– Take business context into
account
August 10th, 2006, SRI 17
Service Selection
“I need a service with encryption key ≥ 128 bits, response time < 10s andprice < ´5 Euro”
encryption key ≤ 512 bits response time = 5sprice = 3 Euro
Automatic selection and negotiation of configurable Web services requires:
Preference information within the admissible range Cardinal preferences to make multi-attributive decisions
Agent
WS Provider I
encryption key = 128 bits response time = 3sprice = 4 Euro
WS Provider II
What key length should be chosen?
Is a 2 sec. improvement in response time worth 1 Euro of additional cost?
August 10th, 2006, SRI 18
Policies for Service Selection
Scoring Policy:maxPrice(key,rt) = 0.1*key+0.7*rt
Pricing Policy
minPrice(key,rt) = 0.05*key+0.04rtAgent
WS Provider I
encryption key = 128 bits response time = 3sprice = 4 Euro WS Provider II
We distinguish between • Scoring Policies: Rules determine which configurations are
admissible and the willingness to pay for a certain configuration • Pricing Policies: Rules that determine what configurations are
provided and their actual price
Challenge: How can we model scoring and pricing policies using Web standards and use them in the decision making process.
August 10th, 2006, SRI 19
Preference-based Selection
• Matchmaker needs to know– How does the price depend on service properties? (Pricing
Policies)
– How does requester’s willingness to pay depend on service properties? (Scoring Policies)
• Matchmaker ranks, e.g., services according to scoring policy
Encode these policies in requests and offers
Our Approach: Policy Ontology Utility Function Policies (Allows deriving rankings, assess absolute suitability,
conflict resolution)Declarative approach based on a foundational ontology (high degree of
axiomatization)
Internet standards: XML, OWL-DL, SWRL (DL-safe subset)Policy enforcement based on logical reasoning using KAON2 reasoner
August 10th, 2006, SRI 20
Modeling Utility Functions
How to model a utility function with ontologies?
Function
PointpolicyValue : Datatypevaluation : Float
next
PiecewiseLinearFunction
constitutedBy constitutedBy
PatternBasedFunction
patternIdentifier : StringpatternParameter1 : Float.patternParameterN : Float
010s
1
5s policyValue
valuation
PointBasedFunction
yes no
1
policyValue
valuation
0 10s
1
5s
valuation
policyValue
AttributePolicyisEvaluated
WRTdefines
defines
August 10th, 2006, SRI 22
Outline
• Semantic Technologies and Services @ Karlsruhe
• Services Vision and its Challenges• Semantic Services
– Service Matching– Semantic Business Process
Management– Semantic Compliance Management
• Conclusion
August 10th, 2006, SRI 23
Matchmaking using the business context
contextual requirements
Pricing policy:“Pay no more than 1K EURO“ “Sell low quality for low price“
Business goal: “High quality of the process“
Provider 1
Provider 2
Provider n
Sales order
Delivery
Picking
Shipment
Packing
Routing
August 10th, 2006, SRI 24
Big picture: Contextualized Business
Policies
business process
business rules
business strategy
business goals
Vertical information integration
business innovatio
n
business collaboration
August 10th, 2006, SRI 26
Outline
• Semantic Technologies and Services @ Karlsruhe
• Services Vision and its Challenges• Semantic Services
– Service Matching: Discovery and Selection– Semantic Business Process Management– Semantic Compliance Management
• Conclusion
August 10th, 2006, SRI 27
Compliance Management
• „Through 2008, investigation of new technologies will slow as discretionary budgets divert to regulatory compliance.… in many case, discretionary IT budgets are entirely consumed by compliance efforts …“
Source: Gartner's Top Predictions for 2006 and Beyond
• e.g. Sarbanes Oxley, Basel II
• Drawbacks of existing solutions for the automation of ComplMgm– non-flexibility due to hard coding of regulations– non-reusability due to lack of a formal description– possible inconsistencies due to an isolated view on the
regulations A formal approach is needed
August 10th, 2006, SRI 28
Semantic Compliance Management: general approach
Policies
Semantic policy model
Semantic business process model
Target domain
Automatic C
ompliance check
August 10th, 2006, SRI 29
Compliance Management for Internal Controls
• Sarbanes Oxley (SOX) and related Compliance Requirements are an Implementation for Management of Internal Controls forced by Law
• COBIT (Control Objectives for Information and related Technology) serves as conceptual framework
– Example for an Application Control (AC):
„Each Purchase Order (PO) with an amount higher than 5000 Euros must be approved by two different Purchasers (Double Check Control)“
• Main Idea: Express Application Controls (ACs) as SWRL-Statements (DL-Safe-Rules) and guard semantic instances of Business Processes during runtime
August 10th, 2006, SRI 30
RiskAdvice. . .
Guarded Sequence (GS)
bp
Semantic Mirror of
bpCS(bp)
Facts(bp)Inference
3
4
GS(bp)
LogsLogs(bp)
2a
2b
1a. . .
Knowledge Base
1b
GA = Guarded Activity is an activity which is in scope of an Application Control (AC) on a Business Process (bp)GS = Guarded Sequence is a sequence of guarded activitiesCS = Control Statement is a logical expression which defines an AC and the reaction on its violation in the form of
Riskii AdvicebpGSacviolationacbpCS ))(,(:),(
StartGA EndGA
Compliance Management for Internal Controls
August 10th, 2006, SRI 32
Outline
• Semantic Technologies and Services @ Karlsruhe
• Services Vision and its Challenges• Semantic Services
– Service Matching– Semantic Business Process Management– Semantic Compliance Management
• Conclusion
August 10th, 2006, SRI 33
Conclusion
Future Work:• Composition of services• Sound theoretical basis for combining
description logics and process algebras• Contract modelling and monitoring• Semantic business process
management– Modeling of strategic knowledge– Semantic monitoring of BPs
August 10th, 2006, SRI 34
Open Questions
• What level of semantic annotation is required– Scalable semantic reasoning– Business value of semantic services– Who will provide the semantic annotations?
• To which extent will business knowledge be formalized– Business rules, strategy, goals
• How to elicit the utility functions?
August 10th, 2006, SRI 35
Main EU Semantic Web Projects in KA
SEKT: Semantically-enabled Knowledge Technologies– €12.5M, 3 year project, 11 European partners (Techn. Coordinator)– http://www.sekt-project.org/
DIP: Data, Information, and Process Integration with Semantic Web Services
– €16.3 M, 3 year project, 17 European partners– http://dip.semanticweb.org/
Knowledge Web– Network of Excellence, €8M, 4 year project, 18 European partners– http://knowledgeweb.semanticweb.org/
X-Media: Knowledge Sharing and Reuse across Media– €13M, 4 year project, 15 European partners– http://nlp.shef.ac.uk/X-Media/index.html
NeOn: Networked Ontologies– €10M, 4 year project, 14 European partners (Techn. Coordinator)– http://www.neon-project.org/
Nepomuk: The Social Semantic Desktop– €11 M, 3 years project, 16 european partners– http://nepomuk.semanticweb.org/
August 10th, 2006, SRI 36
“Shaping the future infrastructures for semantic applications”
The Open University (co-ordinator)University of Sheffield
Universidad Politecnica Madrid,iSOCO, pharmaInnova, Atos Origin
Universitaet Karlsruhe, Software AG, ontoprise, Universitaet Koblenz-Landau
Institut ‘Jozef Stefan’
INRIA Alpes
United Nations FAO, CNR-LOA
Lifecycle Support for Networked Ontologies
• EU IST Integrated Project (FP6)– Start date: March 2006– Duration: 4 year project – Funding: € 10M – http://www.neon-project.org/
• Key outcomes from NeOn– Open, scalable and service-centred reference
architecture– The NeOn toolkit – for engineering contextualized
networked ontologies and semantic applications – Industry-strength documentation and reference material – Three case studies in two sectors:
pharmaceuticals and agriculture/fisheries
August 10th, 2006, SRI 37
Semantic MediaWiki
• MediaWiki used for Wikipedia• Semantic MediaWiki introduces some additional
markup into the wiki-text which allows users to add ”semantic annotations”.
• Structured Knowledge Representation (with RDF export)
• Extensions– for typed Links
• Previously: … Karlsruhe is located in [[Germany]] …• New: … Karlsruhe is located in
[[LocatedIn::Germany]] …– for Annotations
• Previously: … Karlsruhe has 280.000 inhabitants …• New: … Karlsruhe has [[Inhabitants:=280000]] …
August 10th, 2006, SRI 39
References
• Specification of Invocable Semantic Web Resources, Sudhir Agarwal, ICWS 2004
• Automatic Matchmaking of Web Services, Sudhir Agarwal, Anupriya Ankolekar, WWW2006 Poster
• A Policy Framework for Trading Configurable Goods and Services in Open Electronic Markets. Steffen Lamparter, Anupriya Ankolekar, Rudi Studer, Christof Weinhardt, ICEC 2006
• Specification of Access Control and Certification Policies for Semantic Web Services, Sudhir Agarwal, Barbara Sprick, EC-Web 2005
• Towards a Formal Verification of OWL-S Process Models. Anupriya Ankolekar, Massimo Paolucci, Katia Sycara, ISWC 2005
• Automatic Matchmaking of Web Services. Sudhir Agarwal and Rudi Studer. International Conference on Web Services (ICWS 2006)
• Approximating Service Utility from Policies and Value Function Patterns. Steffen Lamparter, Andreas Eberhart, Daniel Oberle, 6th IEEE International Workshop on Policies for Distributed Systems and Networks (POLICY 2005)
• Specification of Policies for Automatic Negotiations of Web Services, Steffen Lamparter, Sudhir Agarwal, Proceedings of the Semantic Web and Policy Workshop at ISWC 2005
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